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A python package for multivariate pattern dependence

Project description

PyMVPD

PyMVPD: MultiVariate Pattern Dependence in Python

MVPD Model Family

  1. Linear Regression Models
  • L2_LR: linear regression model with L2 regularization
  • PCA_LR: linear regression model with no regularization after principal component analysis (PCA)

Workflow

Usage

Example Dataset

Data of one subject from the StudyForrest dataset: FFA - fusiform face area, GM - grey matter.

  • Raw data were first preprocessed using fMRIPrep and then denoised by using CompCor (see more details in Fang et al. 2019).

Example Analyses and Scripts

  1. Choose one MVPD model, set model parameters, input functional data and ROI masks, set output directory in analysis_spec.py;
  2. Run data_loading.py to preprocess functional data;
python3 data_loading.py
  1. Run MVPD model:
sh analysis_exec.sh

Contact

Reach out to mtfang0707@gmail.com for questions, suggestions and feedback.

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